EM Untruncation with Low Demand¶

In this example, we include product and advance purchase (AP) restrictions in the simulation, and have each airline use the leg-based EMSR-B algorithm to manage revenue. Additionally, the EM algorithm is employed to detruncate censored demand. Demand is simulated at a level 50% lower than normal.

In [1]:

import passengersim as pax

pax.versions()

import passengersim as pax pax.versions()

passengersim 0.51.dev11+g921f2a8
passengersim.core 0.51.dev2+g02d3ce20

In [2]:

from passengersim.utils.codeview import show_file

show_file("network/07-untrunc-em-low-demand.yaml")

from passengersim.utils.codeview import show_file show_file("network/07-untrunc-em-low-demand.yaml")

include:
  - 08-untrunc-em.yaml

simulation_controls:
  demand_multiplier: 0.5

In [3]:

sim = pax.Simulation.from_yaml(
    [
        "network/07-untrunc-em-low-demand.yaml",
    ]
)

sim = pax.Simulation.from_yaml( [ "network/07-untrunc-em-low-demand.yaml", ] )

In [4]:

summary = sim.run()

summary = sim.run()

Task Completed after 1.95 seconds

In [5]:

summary.fig_carrier_revenues()

summary.fig_carrier_revenues()

Out[5]:

In [6]:

summary.fig_carrier_load_factors()

summary.fig_carrier_load_factors()

Out[6]:

In [7]:

summary.fig_fare_class_mix()

summary.fig_fare_class_mix()

Out[7]:

In [8]:

summary.fig_bookings_by_timeframe()

summary.fig_bookings_by_timeframe()

Out[8]:

In [9]:

summary.to_xlsx("outputs/3mkt-07.xlsx")

summary.to_xlsx("outputs/3mkt-07.xlsx")

Comparing against Targets¶

In [10]:

import targets

target = targets.load(7, sim.config)

import targets target = targets.load(7, sim.config)

In [11]:

from passengersim import contrast

comps = contrast.Contrast(
    {
        "simulation": summary,
        "target": target,
    }
)

from passengersim import contrast comps = contrast.Contrast( { "simulation": summary, "target": target, } )

In [12]:

contrast.fig_bookings_by_timeframe(comps, by_carrier="AL1")

contrast.fig_bookings_by_timeframe(comps, by_carrier="AL1")

Out[12]:

In [13]:

contrast.fig_carrier_revenues(comps)

contrast.fig_carrier_revenues(comps)

Out[13]:

In [14]:

contrast.fig_fare_class_mix(comps)

contrast.fig_fare_class_mix(comps)

Out[14]:

In [15]:

contrast.fig_bookings_by_timeframe(comps, by_carrier="AL1", by_class=True)

contrast.fig_bookings_by_timeframe(comps, by_carrier="AL1", by_class=True)

Out[15]: